- extend the knowledge of the state of the art in machine learning for data streams; - Development of machine learning models to learn system physics from simulated and measured data (meter, sensors, etc); - Develop transfer learning approaches to construct frugal data-driven models across similar types of loads. - exercise a critical spirit in the evaluation of the research process and the results obtained.
Degree in Electrical Engineering, Informatics, Bioengineering or similar.
Minimum profile required
Proven experience in machine learning and minimum grade of 15 in master course.
Experience in research projects, and writing of scientific papers.
Since 05 Oct 2022 to 19 Oct 2022
Cluster / Centre
Networked Intelligent Systems / Telecommunications and Multimedia